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All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Perceive: Proactive Exploration of Risky Concept Emergence for Identifying Vulnerabilities & Exposures

National databases that collect various kinds of textual threat reports such as ASRS, CERT, and NVD manually process their reports individually. They then offer data products to disseminate the aggregate information, like newsletters, alerts or individual report searching. The goal of this research is to connect these individual reports thematically and temporally to identify emerging or recurring threats, by analyzing large collections of text, source code, collaboration and communication patterns. This capability, I argue, enables us to identify the emergence and recurrence of such themes, and the contexts in which they re-occur, facilitating faster and more capable mitigation. I propose two models to shed light on this goal: An empirical model of vulnerabilities as bugs, the commit flow model, and one of the vulnerabilities and aviation safety threats as topics, the topic flow model. I use as gold standard existing manual workflows in both domains, reflected in the existing data products by these organizations, and empirically evaluate if the automated model scan match or outperform existing manual practices.

ASRS↗
NASA NTRS2008

Intelligent Devices - Sensors and Actuators - A KSC Perspective

The primary objective of this workshop is to identify areas of advancement in sensor measurements and technologies that will help to define standard practices and procedures that will better enable the infusion into flight programs of sensors with improved capabilities but limited or no flight heritage. These standards would be crucial to demonstrating a methodology for validating current models while also creating the possibility of being able to have sufficient data to either update these models (e. g., spatial or temporal resolution, etc.) or develop new models based on the ability to simulate the new measured physical parameters. The workshop is also intended to narrow the gap between sensor measurements (and techniques), data processing techniques and the ability to make use of that data by gathering together experts in the field for a short workshop. This collaboration will unite NASA and other government agencies with contractor capabilities industry-wide to prevent duplication, spawn synergistic growth in sensor technology, help analysts make good engineering decisions and help focus new sensor maturation efforts to better meet future flight program customers' needs. This is the first such workshop designed to specifically address establishing a standardized protocol/methodology for demonstrating the technology readiness of non-flight heritage sensor systems. While other similar workshops are held covering many areas of interest to the sensor development community, no other meeting is specific enough to address this vital but often overlooked topic. By encouraging cross-fertilization of ideas from instrument experts from many different backgrounds, it is hoped that this workshop will initiate innovative new ideas and concepts in sensor development, calibration and validation. It is anticipated this workshop will repeat periodically as needed.

Mata, Carlos T.↗
DOE OSTI2020

Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations

We developed a new class of physics-informed generative adversarial networks (PI-GANs) to solve forward, inverse, and mixed stochastic problems in a unified manner based on a limited number of scattered measurements. Unlike standard GANs relying solely on data for training, here we encoded into the architecture of GANs the governing physical laws in the form of stochastic differential equations (SDEs) using automatic differentiation. In particular, we applied Wasserstein GANs with gradient penalty (WGAN-GP) for its enhanced stability compared to vanilla GANs. We first tested WGAN-GP in approximating Gaussian processes of different correlation lengths based on data realizations collected from simultaneous reads at sparsely placed sensors. We obtained good approximation of the generated stochastic processes to the target ones even if there is a mismatch between the input noise dimensionality and the effective dimensionality of the target stochastic processes. We also studied the overfitting issue for both the discriminator and the generator, and we found that overfitting occurs also in the generator in addition to the discriminator as previously reported. Subsequently, we considered the solution of elliptic SDEs requiring approximations of three stochastic processes, namely the solution, the forcing, and the diffusion coefficient. Here again, we assumed data collected from simultaneous reads at a limited number of sensors for the multiple stochastic processes. Furthermore, three generators were used for the PI-GANs: two of them were feed forward deep neural networks (DNNs), while the other one was the neural network induced by the SDE. For the case where we have one group of data, we employed one feed forward DNN as the discriminator, while for the case of multiple groups of data we employed multiple discriminators in PI-GANs. We solved forward, inverse, and mixed problems without changing the framework of PI-GANs, obtaining both the means and the standard deviations of the stochastic solution and the diffusion coefficient in good agreement with benchmarks. In this work, we have demonstrated the effectiveness of PI-GANs in solving SDEs for about 120 dimensions. In principle, PI-GANs could tackle very high dimensional problems given more sensor data with low-polynomial growth in computational cost.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1990

Advanced telemetry systems for payloads. Technology needs, objectives and issues

The current trends in advanced payload telemetry are the new developments in advanced modulation/coding, the applications of intelligent techniques, data distribution processing, and advanced signal processing methodologies. Concerted efforts will be required to design ultra-reliable man-rated software to cope with these applications. The intelligence embedded and distributed throughout various segments of the telemetry system will need to be overridden by an operator in case of life-threatening situations, making it a real-time integration issue. Suitable MIL standards on physical interfaces and protocols will be adopted to suit the payload telemetry system. New technologies and techniques will be developed for fast retrieval of mass data. Currently, these technology issues are being addressed to provide more efficient, reliable, and reconfigurable systems. There is a need, however, to change the operation culture. The current role of NASA as a leader in developing all the new innovative hardware should be altered to save both time and money. We should use all the available hardware/software developed by the industry and use the existing standards rather than inventing our own.

Source record↗
DOE OSTI2025

Unpacking model inadequacy: The quantification of silver release from TRISO fuel by considering empirical and mechanistic approaches

Increasing adoption of the proposed tristructural isotropic (TRISO) particle fuel for both advanced and existing reactors makes it critical to assess and address any uncertainties and inadequacies of TRISO fission product release models. Model inadequacy stems from simplifications made to the computational model when compared to the experiments. The modeling and simulation efforts conducted using the BISON fuel performance code, along with the experimental campaigns carried out under the Advanced Gas Reactor Fuel Development and Qualification Program, afford a unique opportunity to conduct a rigorous modeling inadequacy assessment within the Bayesian uncertainty quantification (UQ) framework. Here, this study compares the standard Bayesian framework against the Kennedy-O'Hagan (KOH) framework, which explicitly represents modeling inadequacy, in regard to UQ for TRISO silver release models. For this purpose, both the traditional Arrhenius equation fitted to experimental data and the more advanced lower-length-scale (LLS)-informed model, which considers microstructure information, are independently considered. Applying the inverse UQ process on the AGR-2 and -3/4 datasets revealed modeling inadequacy to be the most dominant source of uncertainty. Experimental noise uncertainty is also significant; however, model parameter uncertainty can be considered negligible. Interestingly, both the Arrhenius equation and the LLS-informed model demonstrated similar levels of modeling inadequacy. For the forward predictive UQ, the KOH framework improved both the accuracy and quality of quantified uncertainties in comparison to the standard Bayesian framework. This is true for both the Arrhenius equation and the LLS-informed model. In comparing these modeling approaches, both demonstrated similar performance at the engineering scale, while the LLS-informed model expectedly outperformed the Arrhenius equation at the mesoscale. These conclusions highlight the importance of explicitly accounting for modeling inadequacy in the UQ process, and reinforce the need for continuous refinement of physics-based models in order to address the modeling inadequacy.

Advanced reactors↗
NASA NTRS1975

USDI DCS technical support: Mississippi Test Facility

The objective of the technical support effort is to provide hardware and data processing support to DCS users so that application of the system may be simply and effectively implemented. Technical support at Mississippi Test Facility (MTF) is concerned primarily with on-site hardware. The first objective of the DCP hardware support was to assure that standard measuring apparatus and techniques used by the USGS could be adapted to the DCS. The second objective was to try to standardize the miscellaneous variety of parameters into a standard instrument set. The third objective was to provide the necessary accessories to simplify the use and complement the capabilities of the DCP. The standard USGS sites have been interfaced and are presently operating. These sites are stream gauge, ground water level and line operated quality of water. Evapotranspiration, meteorological and battery operated quality of water sites are planned for near future DCP operation. Three accessories which are under test or development are the Chu antenna, solar power supply and add-on memory. The DCP has proven to be relatively easy to interface with many monitors. The large antenna is awkward to install and transport. The DCS has met the original requirements well; it has and is proving that an operation, satellite-based data collection system is feasible.

Preble, D. M.↗
NASA NTRS1995

Scientific Visualization and Computational Science: Natural Partners

Scientific visualization is developing rapidly, stimulated by computational science, which is gaining acceptance as a third alternative to theory and experiment. Computational science is based on numerical simulations of mathematical models derived from theory. But each individual simulation is like a hypothetical experiment; initial conditions are specified, and the result is a record of the observed conditions. Experiments can be simulated for situations that can not really be created or controlled. Results impossible to measure can be computed.. Even for observable values, computed samples are typically much denser. Numerical simulations also extend scientific exploration where the mathematics is analytically intractable. Numerical simulations are used to study phenomena from subatomic to intergalactic scales and from abstract mathematical structures to pragmatic engineering of everyday objects. But computational science methods would be almost useless without visualization. The obvious reason is that the huge amounts of data produced require the high bandwidth of the human visual system, and interactivity adds to the power. Visualization systems also provide a single context for all the activities involved from debugging the simulations, to exploring the data, to communicating the results. Most of the presentations today have their roots in image processing, where the fundamental task is: Given an image, extract information about the scene. Visualization has developed from computer graphics, and the inverse task: Given a scene description, make an image. Visualization extends the graphics paradigm by expanding the possible input. The goal is still to produce images; the difficulty is that the input is not a scene description displayable by standard graphics methods. Visualization techniques must either transform the data into a scene description or extend graphics techniques to display this odd input. Computational science is a fertile field for visualization research because the results vary so widely and include things that have no known appearance. The amount of data creates additional challenges for both hardware and software systems. Evaluations of visualization should ultimately reflect the insight gained into the scientific phenomena. So making good visualizations requires consideration of characteristics of the user and the purpose of the visualization. Knowledge about human perception and graphic design is also relevant. It is this breadth of knowledge that stimulates proposals for multidisciplinary visualization teams and intelligent visualization assistant software. Visualization is an immature field, but computational science is stimulating research on a broad front.

Uselton, Samuel P.↗
NASA NTRS2008

Cell-Detection Technique for Automated Patch Clamping

A unique and customizable machinevision and image-data-processing technique has been developed for use in automated identification of cells that are optimal for patch clamping. [Patch clamping (in which patch electrodes are pressed against cell membranes) is an electrophysiological technique widely applied for the study of ion channels, and of membrane proteins that regulate the flow of ions across the membranes. Patch clamping is used in many biological research fields such as neurobiology, pharmacology, and molecular biology.] While there exist several hardware techniques for automated patch clamping of cells, very few of those techniques incorporate machine vision for locating cells that are ideal subjects for patch clamping. In contrast, the present technique is embodied in a machine-vision algorithm that, in practical application, enables the user to identify good and bad cells for patch clamping in an image captured by a charge-coupled-device (CCD) camera attached to a microscope, within a processing time of one second. Hence, the present technique can save time, thereby increasing efficiency and reducing cost. The present technique involves the utilization of cell-feature metrics to accurately make decisions on the degree to which individual cells are "good" or "bad" candidates for patch clamping. These metrics include position coordinates (x,y) in the image plane, major-axis length, minor-axis length, area, elongation, roundness, smoothness, angle of orientation, and degree of inclusion in the field of view. The present technique does not require any special hardware beyond commercially available, off-the-shelf patch-clamping hardware: A standard patchclamping microscope system with an attached CCD camera, a personal computer with an imagedata- processing board, and some experience in utilizing imagedata- processing software are all that are needed. A cell image is first captured by the microscope CCD camera and image-data-processing board, then the image data are analyzed by software that implements the present machine-vision technique. This analysis results in the identification of cells that are "good" candidates for patch clamping (see figure). Once a "good" cell is identified, a patch clamp can be effected by an automated patchclamping apparatus or by a human operator. This technique has been shown to enable reliable identification of "good" and "bad" candidate cells for patch clamping. The ultimate goal in further development of this technique is to combine artificial-intelligence processing with instrumentation and controls in order to produce a complete "turnkey" automated patch-clamping system capable of accurately and reliably patch clamping cells with a minimum intervention by a human operator. Moreover, this technique can be adapted to virtually any cellular-analysis procedure that includes repetitive operation of microscope hardware by a human.

McDowell, Mark↗
DOE OSTI2020

A deep neural network to search for new long-lived particles decaying to jets

A tagging algorithm to identify jets that are significantly displaced from the proton-proton (pp) collision region in the CMS detector at the LHC is presented. Displaced jets can arise from the decays of long-lived particles (LLPs), which are predicted by several theoretical extensions of the standard model. The tagger is a multiclass classifier based on a deep neural network, which is parameterised according to the proper decay length $\mathrm{c}\tau_0$ of the LLP. A novel scheme is defined to reliably label jets from LLP decays for supervised learning. Samples of pp collision data, recorded by the CMS detector at a centre-of-mass energy of 13 TeV, and simulated events are used to train the neural network. Domain adaptation by backward propagation is performed to improve the simulation modelling of the jet class probability distributions observed in pp collision data. The potential performance of the tagger is demonstrated with a search for long-lived gluinos, a manifestation of split supersymmetric models. The tagger provides a rejection factor of 10 000 for jets from standard model processes, while maintaining an LLP jet tagging efficiency of 30-80% for gluinos with 1 mm $\leq$ $c\tau_0$ $\leq$ 10 m. The expected coverage of the parameter space for split supersymmetry is presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

FAIRification, Quality Assessment, and Missingness Pattern Discovery for Spatiotemporal Photovoltaic Data

The growth of the photovoltaic market has pushed the demand for power forecasting and performance evaluation for a huge population of PV power plants. Many of these power plants have spatiotemporal coherence that can be utilized for improving model accuracy. We have demonstrated in this paper the FAIRification of spatiotemporal PV time series data. Through the creation of a solar power plant ontology, we propose standards for the naming and structure of metadata used to describe the data from these power plants. Using the structure from this ontology, we have developed both R and Python packages for the automation of the FAIRification process. Going further, we have also developed an R package that automates the analysis of the quality of a data set through the designation of letter grades. To solve the issue of data missingness, we propose the use of St-GNN autoencoders to detect and impute missing values from a data set by utilizing data from power plants nearby.

14 SOLAR ENERGY↗
DOE OSTI2022

Analysis of Data Fusion Between Waveform Events and Radionuclide Detections Reported in 2021 by the International Data Centre

During this project, we assessed the percentage of events reported by the International Data Centre (IDC) that are candidates for evaluation using data fusion methods. We calculated the percentage of waveform (seismic, hydroacoustic, infrasound, SHI) events that may be associated with radionuclide (RN) detections and vice versa. For this task, data fusion means identifying RN detections that may be associated with SHI events. The task of producing a fused SHI and RN bulletin is included in the IDC operational manual. As of 2022, the production of a fused event bulletin remains incomplete, largely because methods for producing the bulletin are under development. Nonetheless, simple methods for data fusion have been developed and preliminary software tools are available at the IDC to associate SHI events and RN detections. This report is a first look at the percentage of SHI events that may be candidates for fusion with RN detections or bulletins. One year of IDC bulletin data (2021) is considered in this report. It is important to note that there were no known nuclear explosions during this time period. Hence, we expect that events during this time period would generate SHI and RN signals. If many SHI events are candidates for fusion with RN data, greater priority should be placed on establishing screening procedures before and/or during the fusion process. By contrast, if the number of candidate events is diminishingly small, then data fusion is not a driver for further development of event or detection screening at the IDC. LLNL reviewed the events reported in the Standard Event Bulletin (SEB) and determined which events are candidates for fusion with the Reviewed Radionuclide Reports (RRR). Much of the work involves establishing a metric or metrics for determining whether a Reviewed Event Bulletin (REB) event is a candidate for data fusion.

58 GEOSCIENCES↗
DOE OSTI2021

KS4A-Omics1.0_FspDS682

Soil fungi facilitate the translocation of inorganic nutrients from soil minerals to other microorganisms and plants. This ability is particularly advantageous in impoverished soils, because fungal mycelial networks can bridge otherwise spatially disconnected and inaccessible nutrient hotspots. However, the molecular mechanisms underlying fungal mineral weathering and transport through soil remains poorly understood. Here, we addressed this knowledge gap by directly visualizing nutrient acquisition and transport through fungal hyphae in a mineral doped soil micromodel using a multimodal imaging approach. Here, we observed how a representative of common saprotrophic soil fungi, Fusarium sp. DS 682, exhibited a mechanosensory response (thigmotropism) around obstacles and through pore spaces (~12 μm) in the presence of minerals.This study establishes the significance of fungal biology and nutrient translocation mechanisms in maintaining fungal growth under water and nutrient limitations in a soil-like microenvironment, using a high-throughput multi-omic analysis approach. Data package KS4A-Omics.1.0_FspDS682 (Publication: Fungal Mineral Weathering Mechanisms Revealed Through Direct Molecular Visualization) contents reported here are the first version (1.0) and contain pre- and post-processed data using high throughput data capture technologies for multi-omic analysis and integration, this data package contains raw and post-processed experimental data for X-Ray Absorption Near Edge Structure Spectroscopy (XANES/XRF), Optical Microscopy, Proteomics, Scanning Electron Microscope (SEM), Time-of-Flight Secondary Ion Mass Spectroscopy (ToF-SIMS), X-Ray Diffraction Spectroscopy (XRD) files, and X- Ray Photoelectron Spectroscopy (XPS) using EMSL capabilities. This data package DOI contains a comprehensive collection of high-throughput multi-omics data and process metadata catalog. Support files include additional data download contents “Read Me” with dataset descriptor information and data source method application ontologies (see data dictionary section). Reported data download content is structured for compliance with reported guidelines provided by community standard initiatives and publisher stakeholder policies supporting FAIR data principles.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

The R -process Alliance: A Nearly Complete R -process Abundance Template Derived from Ultraviolet Spectroscopy of the R -process-enhanced Metal-poor Star HD 222925 *

We present a nearly complete rapid neutron-capture process (r-process) chemical inventory of the metal-poor ([Fe/H] = -1.46 ± 0.10) r-process-enhanced ([Eu/Fe] = +1.32 ± 0.08) halo star HD 222925. This abundance set is the most complete for any object beyond the solar system, with a total of 63 metals detected and seven with upper limits. It comprises 42 elements from 31 ≤ Z ≤ 90, including elements rarely detected in r-process-enhanced stars, such as Ga, Ge, As, Se, Cd, In, Sn, Sb, Te, W, Re, Os, Ir, Pt, and Au. We derive these abundances from an analysis of 404 absorption lines in ultraviolet spectra collected using the Space Telescope Imaging Spectrograph on the Hubble Space Telescope and previously analyzed optical spectra. A series of appendices discusses the atomic data and quality of fits for these lines. The r-process elements from Ba to Pb, including all elements at the third r-process peak, exhibit remarkable agreement with the solar r-process residuals, with a standard deviation of the differences of only 0.08 dex (17%). In contrast, deviations among the lighter elements from Ga to Te span nearly 1.4 dex, and they show distinct trends from Ga to Se, Nb through Cd, and In through Te. The r-process contribution to Ga, Ge, and As is small, and Se is the lightest element whose production is dominated by the r-process. The lanthanide fraction, log X La = -1.39 ± 0.09, is typical for r-process-enhanced stars and higher than that of the kilonova from the GW170817 neutron-star merger event. We advocate adopting this pattern as an alternative to the solar r-process-element residuals when confronting future theoretical models of heavy-element nucleosynthesis with observations.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1974

Square-root algorithm for evaluating mismodeled process noise

As the application of sequential filters has grown, the need has arisen to evaluate the sensitivity of these filters to mismodeling of the random process. A numerically reliable square-root algorithm is developed for calculating the covariances of estimates from a sequential filter which incorrectly models process noise. Mismodeling is restricted to the correlation time and standard deviation of a random process represented as a first-order Gauss-Markov sequence. Using a computer program which employs this algorithm, a sensitivity analysis was performed for several types of earth-based tracking data from an interplanetary spacecraft.

Thornton, C. L.↗
NASA NTRS1979

Chemical-vapor deposition of silicon from silane

Report lists tables of standard free-energy change, equilibrium constant, and heat of reaction for chemical vapor deposition (CVD) of silicon from silane over temperature range of 100 to 1000 K. Data indicates silicon CVD may be a commercially economical process for production of silicon for solar arrays and other applications.

Hsu, G. C.↗
NASA NTRS1988

PiFEx data and archival formats

A standard archival format is presented for the Jet Propulsion Laboratory Mobile Satellite Experiment (MSAT-X) Pilot Field Experiments (PiFEx), which will overcome the deficiencies of the current set-up. This format allows ease of data processing, flexibility for future experiments, and controllable data dissemination to other researchers.

Berner, Jeff B.↗
NASA NTRS1989

Estimating laser transit anemometry noise performance capabilities

A Monte Carlo based LTA (laser transit anemometry) simulation system has been used to perform a detailed evaluation of a set of processing algorithms proposed by Mayo and Smart (1984) for the extraction of two-dimensional flow parameters from LTA data sets collected in a plane normal to the optical axis of the system. The present evaluation includes data ensembles containing 0.0, 5.0, 10.0, and 20.0 percent background noise levels in the constituent correlograms. The results of these evaluations indicate that for turbulence levels of up to 10.0 percent the processing system is able to extract the necessary flow parameters accurately from the LTA data sets. Mean velocity magnitude and flow angle are measurable to within 2.0 percent for turbulence intensity levels of up to 14.0 percent. Standard deviations are measureable to within 10.0 percent over a turbulence range of 3.0-10.0 percent at the same noise levels. These results indicate that the algorithms described have applications in fluid flow surveys.

Humphreys, William M., Jr.↗
NASA NTRS1992

Magnetic tape

The move to visualization and image processing in data systems is increasing the demand for larger and faster mass storage systems. The technology of choice is magnetic tape. This paper briefly reviews the technology past, present, and projected. A case is made for standards and the value of the standards to users.

Robinson, Harriss↗